Forum Discussion

raghad's avatar
raghad
Icon for New Contributor rankNew Contributor
1 month ago

Is Spatial IP ready for LLM / transformer inference?

I am using FPGA AI Suite 2026.1.1 (with the new spatial compiler). Most of the FPGA AI Suite handbook examples I see are classical CNN / vision flows (ResNet-style) on PCIe, hostless JTAG, and SoC. ...
ai suite
general
DomiP_Altera's avatar
DomiP_Altera
Icon for New Contributor rankNew Contributor
1 month ago

Currently FPGA AI Suite 2026.1.1 (with the new spatial compiler) doesn't support LLM / transformer inference.

  • raghad's avatar
    raghad
    Icon for New Contributor rankNew Contributor
    1 month ago

    Could you please clarify:

    • Is LLM inference unsupported across all FPGA AI Suite releases, or is this something being actively worked on for a future release?
    • Can I confirm that the standard FPGA AI Suite workflow is not supported for LLM / Transformer models on the Agilex 5 E-Series 065B Modular Development Kit?
      The workflow I am referring to is:

    Hugging Face model(optimum-intel) → OpenVINO IR (.xml + .bin) → architecture_optimizer → dla_compiler (Sequential flow) or Spatial Compiler → Integrate the generated FPGA AI Suite IP into a Quartus Prime project → Generate the bitstream and program it onto the Agilex 5 E-Series 065B board → Run inference using the FPGA AI Suite runtime (host application).

    • I understand this may not be a push-button process and could require significant modifications to the generated RTL — but is this workflow still considered a viable starting point for implementing LLM / Transformer inference on the Agilex 5 E-Series 065B?

    Thank you very much.